Learning mappings in brain machine interfaces with echo state networks by Rao, Y.N., Kim, S.-P., Sanchez, J.C., Erdogmus, D., Principe, J.C., Carmena, J.M., Lebedev, M.A., Nicolelis, M.A.

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An Info-Gap Approach to Linear Regression by Zachsenhouse, M., Nemets, S., Yoffe, A., Ben-Haim, Y., Lebedev, M.A., Nicolelis, M.A.

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Multiresolution Representations and Data Mining of Neural Spikes for Brain-Machine Interfaces by Sung-Phil Kim, Carmena, J.M., Nicolelis, M.A., Principe, J.C.

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Continuous shared control for stabilizing reaching and grasping with brain-machine interfaces by Kim, H.K., Biggs, J., Schloerb, W., Carmena, M., Lebedev, M.A., Nicolelis, M.A.L., Srinivasan, M.A.

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Ascertaining the importance of neurons to develop better brain-machine interfaces by Sanchez, J.C., Carmena, J.M., Lebedev, M.A., Nicolelis, M.A.L., Harris, J.G., Principe, J.C.

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The Muscle Activation Method: An Approach to Impedance Control of Brain-Machine Interfaces Through a Musculoskeletal Model of the Arm by Kim, Hyun K., Carmena, Jose M., Biggs, S. James, Hanson, Timothy L., Nicolelis, Miguel A. L., Srinivasan, Mandayam A.

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Simultaneus prediction of four kinematic variables for a brain-machine interface using a single recurrent neural network by Sanchez, J.C., Principe, J.C., Carmena, J.M., Lebedev, M.A., Nicolelis, M.A.L.

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